Despite the extensive use in oceanographic-atmospheric
modeling, computational fluid dynamics simulation, and electro-magnetic
field analysis, flow visualization remains one of the most challenging
research topics of SciVis due to the daunting task of conveying the flow
direction, particularly in three-dimensional senarios, in a visually understandable
way. Thus the major goal is to design novel flow representation schemes
to depict directional information in a perceptually effective manner.
Important issues include efficiency (computational
speed and memory cost), increasingly large datasets and sophisticated
demands, time-varying or unsteady flows, complex grids and multivariate
(e.g., velocity, temperature, pressure, density, and viscosity) visualization,
and feature extraction and tracking.

Iso-surface (extraction) and (Direct)
Volume Rendering are two classical methods for visualizing volume
data. Iso-surface techniques such as Marching Cubes, Dividing Cubes, and
Marching Tetrahedra work by fitting intermediate geometric primitives (e.g.,
triangles) to any reconstructed surface prior to a rendering procedure.
Volume rendering techniques such as Ray Casting, Splatting, Cell Projection,
Shear-Warp, and hardware-based (e.g., Graphical Processing Unit, GPU)
2D / 3D texture mapping eliminate the need for the construction of any intermediate
representation, but instead operate directly on voxels (volume elements,
the 3D counterpart of "pixels") by employing a light absorption-emission
model and a transfer function (i.e., a map / transform used to emphasize
or suppress part of the data from the rest) to assign colors and opacities
to the voxels that are then sampled and composited or blended (through integral
convolution) along the viewing direction. Volume segmentation and registration,
automatic but effective transfer function design, and robust feature extraction
and tracking are still open problems.

CT (Computerized Tomography)
plays an important role in Computer-Aided Diagnosis and healthcare clinics.
As a set of rays are cast from a rotating CT scanner to pass through tissues,
bones, and whatever organs, the source radiological intensities attenuate
to what are measured at the exit by an array of detectors to produce projection
data, from which a Filtered Back-Projection method based on Fourier Slice
Theorem is typically adopted to reconstruct, in frequency domain, a stack
of slice images. Compared to Equi-Angular Fan Beam, Equi-Spatial Fan Beam,
Cone Beam, and Single-Slice Helical Scan, Multi-Slice Helical Scan is a
more powerful acquisition approach because of the accelerated scanning process
(which greatly reduces the patient's discomfort) and the increased temporal-spatial
resolution. An ambitious effort in the CT imaging community is to reconstruct
a sequence of high-fidelity images of a motion organ (e.g., lung) from multi-slice
spiral CT scan.